# Simulating Planetary Motion (Using Code!)

###### Simulating Newton’s Law of Universal Law of Gravity

Interactive simulations (like those created by the University of Colorado – PhET) can be really nice for impressing students, and giving them a way to explore the dynamics of a simulation. If incorporated into a lesson well, they can add to the active learning process. The question that I always struggle with though is “are the students learning how the simulation works, or are they learning how nature works?”

I have a nagging feeling that the students would possibly get more out of being able to see the simulation source code, specifically the rules of behavior of the simulation, and then through “tweaking” the code, see how those rules govern behavior. I would like to develop curriculum that would allow my students more opportunities to explore the code “behind” the simulations. This presents a few challenges that have been identified by other great physics educators, and if you are thinking about doing the same thing – I would suggest reviewing their insights. I include a quote from Ruth Chabay’s brief, but very interesting article on this topic:

To integrate computation, especially programming, into an introductory course, it is necessary to minimize the amount of non-physics related material that must be taught. To do so it is necessary to teach a minimal subset of programming constructs; employ an environment and language that are easy to learn and use; ensure that program constructs match key physics constructs; provide a structured set of scaffolded activities that introduce students to programming in the con- text of solving physics problems

This was my first attempt at doing just this, and I had some success and realized that I have some work to do.

# Which Code?

A popular programming language in the Physics Modeling community is VPython. I have chosen to use a different language to use called Processing. There are reasons I chose this language, but I am sure there are reasons one would choose VPython (or other languages). At this point, I have not had the opportunity to work with VPython, so this post will not attempt to compare Processing to other languages. Perhaps I will do so in the future…

Here are some general reasons why I like Processing:

1. It’s free and open source.
2. Because its built on a visual programming interface, its really easy for the students to create visual content on the screen, and it is very easy to create visual animations due to the embedded “draw” loop.
3. The official website has great examples and tutorials. It is full of great code samples and quick tutorials. You can loose yourself for hours (or days!) just having fun exploring the examples and tutorials.
4. The IDE is simple and very similar to the Arduino IDE, so if you plan on doing any Arduino programming, the similarity is nice for the students.
5. There is a nice vector library for doing vector operations (.add, .mult, .norm, .dot, etc.)
6. Its object oriented so that you can have the added benefit of teaching important programming concepts – though this might be why some people might not like it.

# The Simulation

The simulation that the students were introduced to was a simulation that modeled Newton’s Law of Universal Gravitation. The students were given some instructions on the basic structure of the program, and I made sure that there was some guiding comments embedded in the code. This program was inspired/adapted from a similar program created by Daniel Shiffman who has also written an amazing book on simulating nature through code called Nature of Code.

The program defines two classes. First, there is the parent class called Particle. This class defines some basic attributes like location, velocity and acceleration as well as mass. It also has some basic functions that allow it to move and allow it to respond to a force. The second class is the child class called Planet. It can do everything that a Particle can (because it inherits from the Particle class), but it can also exert an attractive force on other Planets.  Here is the code below:

```/* A parent class for all moving particles
class Particle {
PVector location;
PVector velocity;
PVector acceleration;
float mass;

Particle(float x, float y, float m) {
mass = m;
location = new PVector(x, y);
velocity = new PVector(0, 0);
acceleration = new PVector(0, 0);
}

void applyForce(PVector force) {
// Newton’s second law at its simplest.
PVector f = PVector.div(force,mass);
}

void move() {
acceleration.mult(0);
}
}

/**
This class defines an object that behaves like a planet.
Planet objects extend Mover objects, so they can move. They
also can attract other planet objects.
**/

class Planet extends Particle {

float size;
float G = 1;

// To create a planet, you need to supply coordinates, mass, and size
Planet(float x, float y, float m, float s) {
super(x, y, m);
size = s;
}

// This function allows a planet to exert an attractive force on another planet.
PVector attract(Planet p) {

// We first have to figure out the direction of the force
// This creates a unit vector for the direction
PVector force = PVector.sub(this.location, p.location);
float distance = force.mag();
distance = constrain(distance,size + p.size,500);
force.normalize();

// This is where we use Newton's Law of Universal Gravitation!
// The stength of the attraction force is proportional to the
// product of the mass of this planet and the mass of the other planet
// as well as the value of G. It is also inverseley proportional to
// the distance squared.
float strength = (G * mass * p.mass) / (distance * distance);

// To get the final force vector, we need to
// multiply the unit vector by the scalar strength
force.mult(strength);

// Return the force so that it can be applied!
return force;
}

// Just displays the planet as a circle (ellipse)
void display() {
stroke(255);
fill(255, 100);
ellipse(location.x, location.y, size/2, size/2);
}

}

/**
This program simulates the gravitational interaction between planet objects
**/

Planet planet1;
Planet planet2;

void setup() {
background(0);
size(800,800);
// Inputs for each planet:
planet1 = new Planet(width/2,height/4,6000,60);
planet2 = new Planet(width/2,height/1.25,6000,60);

// This is where you can change the initial velocities of the planets.
planet1.velocity.x = 0;
planet1.velocity.y = 0;
planet2.velocity.x = 0;
planet2.velocity.y = 0;
}

void draw() {
background(0);

// f1 is a force vector that is created by calling the planet's attract function
PVector f1 = planet1.attract(planet2);
// Now apply that force on the other planet.
planet2.applyForce(f1);
// Now deal with the opposite force pair
PVector f2 = PVector.mult(f1, -1);
planet1.applyForce(f2);

// Allow the planets to now move.
planet1.move();
planet2.move();

// Display the planets
planet1.display();
planet2.display();
}```

# Experimenting With The Code

The students could change the initial values of the planets, such as the starting positions, the masses and radii by changing the input values of these two lines of code:

```planet1 = new Planet(width/2,height/4,6000,60);
planet2 = new Planet(width/2,height/1.25,6000,60);```

The planets initial velocities could also be modified by changing the values assigned in these four lines of code:

```planet1.velocity.x = 0;
planet1.velocity.y = 0;
planet2.velocity.x = 0;
planet2.velocity.y = 0;```

The code that actually guides the strength of the gravitational attraction between the two planets is actually very simple. This is the magnitude of the force as defined by Newton’s Law of Universal Gravity in code:

`float strength = (G * mass * p.mass) / (distance * distance);`

There is some slightly complicated code that controls the direction of the force and how that force is then applied to the planet object’s state of motion, but I didn’t have the time to explain this, which was a bit disappointing (see below).

# For The Future

I am currently really interested in incorporating programming into the academy program, but have found myself a bit intimidated by the challenges identified by Ruth Chabay. The most significant challenge is time:

In an already full introductory physics curriculum, there is little or no time to teach major programming skills. Students who are new to programming are also new to the process of debugging; teaching debugging strategies requires even more time…Working on programming activities only once a week in a lab or recitation section may not be adequate to keep knowledge of syntax and program structure fresh in the students’ minds.

I plan on taking some time this summer to see how I could integrate computer programming more significantly into the curriculum without causing the learning of Physics to suffer – that would of course defeat the purpose!

# Overview: What is Common? Argumentation

You might be one of the many Americans that are a bit perplexed by this whole new Common Core State Standards (CCSS) “stuff”. In this post I will try my best to explain how I designed an assessment for the first year students in the Academy that aligns with the Common Core. This was partly motivated by a district wide push to bring all curriculum in alignment with the CCSS, specifically as it relates to literacy.

For context, I will identify the educational goal that in part motivated this effort. Our school site administration has identified argumentation as a key curricular focus that all staff will address this year. This has given the school the ability to focus on literacy and has allowed the school staff to guide their efforts towards a collaborative goal.

This assessment was organized into three parts: the prediction, the analysis, and the reflection. Each part of the assessment focused on specific standards.

# Part 1: The Prediction Report

If you haven’t had a chance to read a previous post where I describe how the students conducted experiments and collected data pertaining to building a predictive model, then I might suggest it, as it is really the first part of this assessment.

The standards addressed in this part of the assessment are as follows:

CCSS.ELA-Literacy.RST.11-12.3
Follow precisely a complex multistep procedure when carrying out experiments, taking measurements, or performing technical tasks; analyze the specific results based on explanations in the text.

CCSS.ELA-Literacy.RST.11-12.7
Integrate and evaluate multiple sources of information presented in diverse formats and media (e.g., quantitative data, video, multimedia) in order to address a question or solve a problem.

To summarize the first part of the assessment, the students were required to collect data in order to create a prediction report describing the performance of their model rockets. The report had to include these elements:

1. Force diagrams (free-body diagrams) depicting the predicted forces acting on the rocket during the a) thrust phase, b) cruise phase, and c) descent phase.
2. Net force equations that identify the causal relationship governing the motion state of the rocket.
3. Three motion graphs depicting the predicted behavior of the rocket. This included its predicted acceleration, velocity and position as a function of time.

The student teams submitted these reports prior to the actual launch.

# Part 2: Analysis Report

The next step was to run the actual experiment – the launching of the rockets! Although the launch day was soggy, we still had a successful afternoon, and we got some great data. The details of the launch are described in a previous post.

The standard addressed in this part of the assessment was as follows:

CCSS.ELA-Literacy.RST.11-12.9
Synthesize information from a range of sources (e.g., texts, experiments, simulations) into a coherent understanding of a process, phenomenon, or concept, resolving conflicting information when possible.

The students were given their prediction reports back, and then also given the data from the small altimeters that were used to collect altitude data. The students were then asked to create an analysis of their rocket’s performance:

This report required these elements:

1. Using the data analysis tools in LoggerPro, they had to identify:
1. The acceleration of the rocket during the thrust phase (a best estimate)
2. The acceleration of the rocket during the cruise phase (a best estimate)
3. The maximum velocity of the rocket (a best estimate)
4. The descent velocity (a best estimate)
2. A velocity vs time graph from the information above.
3. An acceleration vs time graph.

# Part 3: Reflection (Addressing Counter-claims)

The final part of the assessment asked the students to compare the prediction and analysis reports and then propose reasons for discrepancies between the data. I also asked the students to respond to some Aristotelian counter claims by using their data and the models that we had collectively established in class.

The standards addressed in this part of the assessment were:

CCSS.ELA-Literacy.RST.11-12.8
Evaluate the hypotheses, data, analysis, and conclusions in a science or technical text, verifying the data when possible and corroborating or challenging conclusions with other sources of information.

CCSS.ELA-Literacy.WHST.9-10.1.a
Introduce precise claim(s), distinguish the claim(s) from alternate or opposing claims, and create an organization that establishes clear relationships among the claim(s), counterclaims, reasons, and evidence.

I asked the students to respond to the following questions which required that the students use data to support their analysis.

1. Compare the predicted NET force on your rocket during the thrust phase to the actual NET force on your rocket during the thrust phase by using your data – you will need to estimate the actual NET force during this phase. Using these numbers as evidence (you must include these values in your answer), describe at least one reason these values are different.
2. Compare the predicted maximum height of your rocket with the actual maximum by using your data. Using these numbers as evidence (you must include these values in your answer), describe at least one reason these values are different.
3. Compare the predicted descent velocity during the descent phase to the actual descent velocity from your data. Using these numbers as evidence (you must include these values in your answer), describe at least one reason these values are different.
4. Look at your data and then also at your prediction graphs. Describe at least two differences between the graphs, AND WHY you think these differences exist.
5. Based on the actual data you collected, what design changes would you make IF you could create this rocket from scratch again? Give at least two examples of design changes you would make.

I also included two questions that asked the students to respond to an alternative explanation for the behavior of their rocket. These claims were specifically created in order to address student misconceptions involving inertia and residual forces.  Below I have included the questions and example student responses:

Question 1:
“Make a counter claim to the following statement from someone who is an “Aristotelian”: The reason that the rocket continued to move upwards after the fuel had run out is that the fuel force continued to push on the rocket, but lessened until the rocket reached its apex, when the rocket stopped moving and the thrust force disappeared. Once the thrust force disappeared, the rocket began falling back to earth!”

Example Response:
“This is incorrect because as soon as the fuel runs out there is no longer a thrust force acting on the rocket. After the fuel runs out the only force acting on the rocket is the force of gravity which will slow down the rocket until its velocity is zero and then the rocket will continue accelerating downward and fall to the earth.”

Question 2:
“Make a counter claim to the following statement from someone who is an “Aristotelian”:The reason that the rocket descended back to earth is because the rocket is heavier than air and so the force from gravity was greater than any air resistance force on the parachute, thus resulting in the rocket falling back to earth.”

Example Response:
“Actually, the reason the rocket descended to earth is because the forces of gravity and drag were equal. The rocket was falling at terminal velocity, and we know that when an object is traveling at a constant velocity there is no acceleration. If the force of gravity working on the rocket was greater, the rocket would be accelerating in its descent. Knowing that the rocket falls in this way, we can conclude that the forces of gravity and drag working on the parachute were equal.”

# Conclusion

I am very pleased by the students’ performances on this assessment, and many of the students enjoyed the process and appreciated the opportunity to connect their learning and demonstrate their knowledge and skill. I feel that there is much to consider for the next time I do this kind of assessment, which will be at the end of the spring semester.

One area I can quickly see I need to help the students develop is making connections to data more explicit. Most students would justify their arguments by stating that a certain explanation was evident. I need to help them develop the skill of presenting evidence more clearly and then linking their arguments to the actual evidence. This was an implicit practice, but it needs to be more explicit.

I hope to hear from you all about how I might perfect this process, and prepare the students to excel on this kind of authentic, problem based assessment.

Thanks!

# We Have Lift Off!

This is a follow up post to Modeling A Rocket’s Journey – A Synthesis where I described how the students in the first year program were engaged in creating a predictive report for their model rockets. I want to emphasize that these model rockets were not kits. Each rocket was designed using 3D CAD software, and each component was either fabricated from raw material, or was created from material that was not intended for use in model rocketry. The only exception to this is the actual rocket motor.

The next step was to launch the rockets and have the altimeter payload collect altitude data.

# Launch Conditions – A Bit Soggy

Unfortunately the week of our scheduled launch happened to be a week of some pretty hefty rains. We rescheduled the launch twice before finally accepting the soggy launch conditions. With umbrellas and rain jackets, we trudged out to the baseball diamond and got to work setting up for the launch. We had some minor difficulties in the wet weather, but eventually had a very successful launch day.

Most of the rockets were able to launch and deploy their valuable payload – the Pnut Altimeter.

The students seemed very excited to finally see the rockets launch, and to see the successful deployment of the parachutes. Although we all got a little wet and muddy, we had a great time!

# The Altimeter Data

The altimeters use a small barometric pressure sensor to collect altitude data (the altimeters also contain a small temperature sensor and voltage sensor). The altitude is recorded in feet every .05 seconds. Here is an example of one rocket’s recorded flight data:

https://plot.ly/~stemples/9

The students were then asked to use the data to create a comparative analysis report. I will detail how the assignment was set up and also discuss how the students performed on this assignment. That will be for another post.

I want to also thank Mr. Kainz for his amazing photos that are displayed here.

# A Synthesis Of All The Models (Thus Far)

In this post I will describe a culminating activity for the first year students in the Academy. This is really the destination that the students have been headed towards since the beginning of the course. Everything they have learned is synthesized in this activity where the students gather data from various observations/experiments and then use the data to predict their own model rocket’s journey.

Note: There were two significant simplifications that we had to make based on the ability level of the students and the physics content covered in class. We had to assume that there was no air resistance force acting on the rocket during the thrust and cruise phases. We also assumed that the mass of the rocket did not change. I intend to have the students reflect on how this might affect the predictions and then analyze the actual performance data. More on this later…

# Measuring The Rocket Engine Thrust

We first needed to figure out the average force exerted by the rocket motor on the rockets and the time interval during which that force would be applied. This would give the students both the thrust force and the length of time of the thrust phase. We needed to collect force measurements for the rocket motors that we were using (C6-5). You can actually download this from many different websites, but it was much more fun to actually do it ourselves! Mr. Holt made a neat little rocket motor holder that was attached to a force meter and we went out into the rain to test the motor (see video below – thank’s Gary!):

The force data was then shared out to the students – here is what the graph looked like:

And this is the force vs time graph one retailer posted on their website:

Although the students had not been introduced to the concept of Impulse-Momentum transfer, we can use the average force, and that seems to work out really well. Just to make sure we could do this, I used the Integral tool in LoggerPro to measure the impulse, and it came out to 8.83 N s – really close to what Estes states – 8.8 N s.

# A Mini Wind Tunnel Test

The students then needed to measure the drag force on their parachutes (all cut on our new laser cutter) as a function of air speed so that they could estimate the terminal velocity of their rocket during the descent phase.  Next step was to test the parachutes. Luckily, Mr. Holt and I had helped two of our previous students create a really nice wind tunnel. We used a force meter attached to a vertical post inside the tunnel…

…and then we used a little Kestrel anemometer to measure the air speed…

Students were able to increase the air speed in the tunnel by turning a rheostat that controlled the fan speed. They then measured the wind velocity and graphed that against the measured force – just like NASA!

Here is some sample data to show how the results came out – not bad!

Students now had a way to estimate the descent velocity because they could calculate the gravitational force on their rocket, using the measured mass of their rockets, and then they could use their data to find the corresponding wind speed.

# Putting It All Together

As part of their final (50%), the students were asked to then take this data, measure the mass of their model rocket and construct a prediction. The prediction was to include these five elements:

1. A set of force diagrams for the different phases – thrust, cruise, and descent. The diagrams also had to include accompanying net force equations.
2. An acceleration vs time graph.
3. A velocity vs time graph.
4. A position vs time graph.
5. Finally a calculation sheet that includes all calculations required to create the motion graphs.

The students have been asked to turn this in before the actual launch.

As we collected the data above, I never explicitly reveal how the data should be used to make these predictions, but I do give them some guiding questions that orients them. They work with their partner’s on this report, but I warn them that they will both be held responsible for understanding the process of creating the prediction report.

# Testing the Predictions

Each student rocket will be equipped with a small altimeter (from Apogee Rocketry – love this thing!).

This altimeter records altitude data in 1/10 of a second intervals, and we have found it to be very accurate and reliable. We will be launching next week, so tune in soon for an exciting update on how the launches went!

# Torque/Speed Curves

In this post I’m going to describe our attempt to measure the power curve for the DC motors used in the Solar Dragster race this year. I’m going to be honest, our efforts weren’t really that successful, but I can at least say that I learned some things that might help for next year, and I think the students were able to do some authentic device testing – a part of being an engineer.

Last year I was a bit concerned that the DC motors that we were using in the Solar Dragster Race were not actually outputting the same power. I wanted to devise a way to measure the motor power, and then have each team do their own analysis. I wanted the students to do this without understanding the electrical power parameters involved because we were at this point only looking at motors as being a black box that gets energy from a source and transfers that energy into a rotational device – i.e. an axle, then to a gear, then to another axle, and finally to a wheel. I looked into getting a torque sensor, but quickly found out that these cost a fortune!

I came across this interesting website from MIT, which was a nice resource for the theory about DC motor performance. The site does a nice job in explaining torque/speed curves, and how the graph of torque vs angular speed is essentially linear for DC motors. That meant that all the students really needed to do was to measure stall torque and the no load speed of their motors and then we would have the torque/speed curve. The website identifies a device that they custom built for testing motors, and it looks interesting, but I didn’t have time to reverse engineer what they had built and unfortunately the images and videos aren’t clear enough to easily understand how the device works – something perhaps for summer tinkering…

One of the issues with the little DC motors that you buy is that the arbor is really small, and it has no index, so its really hard to attach anything. Generally, you have to go with a friction fitting, and I was worried that doing a stall torque test was going to be difficult. Mr. Holt and I designed and printed out a little lever arm to attach to the motors. This little arm could then be attached to a force meter to measure the stall torque and then also used to help measure the rotational velocity using a Photogate. The final “test-bench” looked like this:

The motors were clamped to a lab stand that was then placed so that the little lever arm would rotate and block the Photogate laser as it spun. This is how the students measured the no load speeds. Then they attached a string to the little hole in the arm, and then attached this to a force meter to get the stall torque. All the motors were tested with essentially the same power source – two AA batteries.

I then had the students share their data using a Google Spreadsheet and I compiled the data – here it is on Plotly:

There is obviously some variability in the motor performance, but its hard to tell if any of the motors give a distinctive advantage over the others because I suspect that the data is not that reliable unfortunately. I do suspect that the angular speed data might be inaccurate due to the fact that we were getting some very differing results from the Photogate. Although we made the sampling rate as rapid as possible, I still am not confident that the Photogate was able to read the blocking of the laser accurately – the motors spin VERY fast (upwards of 5000 RPM’s when not loaded). I’m also not sure if the data then could then be used in any instructive way to help students make design decisions about their dragsters.

Although this may seem like a failure, it did allow the students to identify at least two motors that we knew were malfunctioning, so we were able to swap those out before the competition.

# For Next Year

I think at this point I would want to make some changes to this activity. Although it was somewhat helpful in giving the students a direct interaction with data associated with the performance of a DC motor, and how that performance is calculated at the product of the torque and angular velocity, I’m not sure that the activity supplied data that was good enough to then use as an input factor in the competition. For example, I didn’t feel confident about allowing students to use the calculated maximum input power as a scaling factor for their dragster race time.

Perhaps next year, we can find the funds to purchase a high precision, digital torque meter, or find the time and money to build our own “analog” torque/speed meter like the one that MIT designed. All in all, I’d say this activity was partially successful.

# Appending The Conservative Models

After investigating the causal relationship between torque and angular acceleration, I introduced the possibility to the class that perhaps we also needed to revisit the Energy Transfer Model and the Momentum Transfer Model. The students agreed that an object that is rotating must have energy. This was pretty easy to demonstrate.

I set up a situation in the class where two of the variable inertia disks that we created on the 3D printers were placed at the top of an inclined ramp. The internal marbles were placed at two different configurations inside the disks and then the students predicted which disk would reach the end of the ramp first. I was pleased to find out that the class appeared to agree that the disk with the marbles located closer to the radius would be the winner. I really think that our investigation with the variable inertia disks solidified the students’ conceptual understanding of rotational inertia and the importance of mass distribution.

I have not yet found a good experiment where students could discover the rotational kinetic energy relationship, so I decided to take them through a derivation based on linear kinetic energy. I then asked the students to do some whiteboard work. I asked them to demonstrate that the disks would indeed reach the end of the ramp at different times. Although this wasn’t strictly a constructivist approach, it was good practice in doing some fairly difficult algebra without numerical values – something the students traditionally are not very good at.

We then moved onto momentum. Again, I started by reviewing the Momentum Transfer Model for a particle. At this point the pattern had been fairly well established. The relationship between angular and linear quantities seemed to have taken hold because the students were quick to propose a mathematical definition for angular momentum. Our next goal was to figure out whether this was a conserved quantity.

Mr Holt and I had created a set of metal disks that could be attached to the rotary sensors. I decided to create our own, rather than (sorry Vernier) buy them as I thought that the commercial kit was over priced. It wasn’t too hard to create the disks, especially when you have access to a CNC plasma cutter!

The students attached one disk to the rotary motion sensor and then got that disk spinning. They then took a second disk that had small magnets attached to it, and dropped this disk onto the spinning disk. The students compared the angular velocity before and after the disks were combined and then calculated the angular momentum of the system before and after. The data we got was quite good with the class getting in the range of only about a 5% to 6% difference.

# Wrapping it Up (or Un-Rolling It Down)

As a final deployment, I decided to try the deployment activity that Frank Nochese did with his students. It seemed like a good (and fun) way to wrap up our model (or as I have already argued – models).

Before doing the deployment activity, I reviewed all the model specifics with the students. My point here was to impress on them that what we had not really built a new model, but rather had extended many of the prior particle models to include rigid extended bodies. This generally only required that we consider the moment arm in all the particle models. I think this really helped a number of students see the connection between models that they felt they understood and all this rotational stuff that seemed a bit confusing.

I then set them up with the deployment activity, but I asked them to specifically solve the problem using both energy and net torque. There was some success, but I realized that the task was a bit much for the class. Once again, it is clear that I need to give them more practice with these problems that require multiple steps and that involve algebraic manipulation of symbols without numbers. Plenty of time to practice that!

# Building The Net Force Particle Model (Part 1)

From “The How” to “The Why”:

One of the three projects that the students will complete this year is a custom designed and fabricated rocket. One of the requirements of this project is for the rockets to carry a small solid state altimeter that collects vertical position data. This year I decided to give the students some data collected by last year’s students. Here is what the data looks like from one typical altimeter reading:

As an introduction to this next model, I presented them with the data and asked them to use both the Constant Velocity Particle Model and the Constant Acceleration Particle Model to describe the motion of the rocket based on the data. Students responded to several questions that I created and they posted their answers through the Learning Management System we use.

A Simple Definition, A Simple Representation

The student investigation teams were then asked to draw velocity vs time graphs on their whiteboards. I was impressed to see that most teams were able to interpret the position data and create a velocity graph that agreed with the data. There was some debate about the graphs, but the students worked through these differences and came to consensus around what the graph would most likely look like. At this point I was thinking about using LoggerPro’s ability to graph the derivative of a data set, but decided that I would leave that for a later date, though next year I might do it earlier.

I then introduced a very basic definition of a force:

“A Force is A Push or A Pull”

And then I proposed that we could represent the force with an arrow, just as we had done with velocity and acceleration. I then asked them to divide the rocket data into four sections based on the answers to the questions we had discussed. The students then drew a representation of the rocket in each stage and the forces acting on the rocket. The stages the students identified were 4) on the ground, 3) descending by parachute, 2) going up without fuel, and 1) going up with fuel. I asked them to draw the diagrams by starting at the end. Here is a typical example of the force diagrams the students drew:

The labeling is a standard that is outlined in the Modeling methodology – it reads (type, feeler, dealer).

Constant Velocity Motion and Net Force

We started the class discussion by looking at the forces acting on the rocket when the rocket was on the ground. Students agreed unanimously that there were two forces acting on the rocket – one down, one up – the gravitational force and then the force from the ground. Great. Then on to the descent phase. Certainly less unanimity here. The students again agreed on the number of forces – two – one up from air resistance, one down from gravity. The students quickly got into several back-and-forth arguments about the length of the force vectors. The class was split. Were the forces equal? Or, was gravity “winning”? The big stumbling block was around the question, “if gravity was equal to the air resistance force, then why was the rocket still falling”? A classic example of Aristotelian thinking. I encouraged them to ask the question – “if gravity was winning, why wasn’t the rocket speeding up?” One student proposed that maybe the force of gravity was just ever so slightly larger. Some students pounced in this. They argued that the forces weren’t equal at first, but as the rocket (with parachute) descended, the air resistance force strengthened and eventually became as strong as the gravitational force. the reason the rocket didn’t slow down was because it was already moving when the forces became equal. Awesome. Then a student gave an excellent description of a thought experiment where a box was traveling through space in one direction and convinced the students that the box would not slow down if you pushed equally on both sides of the box. Students reached consensus – the rocket moved at a constant velocity because the forces were equal.

The “Residue” Misconception

We then progressed to the next stage. Things got really interesting. Without exception, ALL the student groups identified an arrow pointing upward, even though they all agreed that the fuel had run out. The question that I think cuts through this the quickest is to ask “who is pushing on the rocket upward?” Most students get that funny look on their faces as their brains begin to realize that they just ran into a logical conundrum. Some students start to respond – “the rocket pushes the rocket.” OK, how? What kind of force is it? A contact force? How does it push or pull itself? The students at this point began to question each other and the room erupted in arguments. Being a bit of a control freak, I’ve had to learn to allow space and time for these chaotic moments, but also realize the importance of catching the class before it descends into something less productive.

At this point, one group erased the upward force. I asked them why they had done this. They responded that they didn’t think a force was needed for the rocket to continue upward, and that gravity and air resistance were slowing the rocket down. This seemed impossible to some of the students. They asked – “but something is left over after the fuel runs out, isn’t there?” The class began to divide up into those that now believed the rocket no longer had any upward force acting on it and those that believed there was some kind of “left-over” force, what I call a “residue”. So, once again, I asked them to identify the dealer of the residue force. The answer is generally – “the fuel”. Ah, but hasn’t the fuel run out? Yes, but the rocket has gained something from the fuel and now that is what is pushing it upward.

This is not such a wild idea, and in fact is not that far from the idea of Kinetic Energy. The students that were in the “no upward force” camp started to explain to the other students in the class that the fuel had “given” the rocket its upward velocity, but now that the fuel was gone, the rocket was now slowing down. We discussed the idea that anything that was slowing down must be experiencing a force pushing in the opposite direction of its velocity. We returned to the thought experiment with the box floating through space. The students debated about whether this box would slow down if the force that had gotten the box moving in the first place disappeared. The students agreed that if there were no forces acting on it to slow it, then it was reasonable to say that it would never slow down. Students then agreed the rocket was no different. It didn’t need a force to continue moving at a constant velocity, but that if it was instead accelerating (in this case in the negative direction) then it would need a force, which was provided by gravity and the air resistance force.  The students began to coalesce around the idea that if a force was a push or a pull, then the rocket that had run out of fuel was not getting pushed any longer, and that although it was moving upward it was indeed accelerating downward.

Making Some Observations

During the next class, I had the students set up a motion detector on one side of a Vernier dynamics track and use a force meter to pull on a low friction cart. They were to also record the velocity of the cart while the students pulled twice in quick succession on a string connected to the cart and force meter.

The students then shared their graphs with the rest of the class:

This experiment is meant to re-enforce some of the arguments made during the previous class. The students quickly see that the velocity is measured to change when the force is applied and that the velocity is “constantish” when no force is applied. The students were ready to tackle how the force and acceleration were quantitatively related, but that’s for another post…